Abstract
Multistatic unmanned aerial vehicle-borne synthetic aperture radar (MuUAV-SAR) plays an important role in the applications of environmental monitoring and disaster warning because its distributed platforms can provide high-resolution imagery by fusing the multiple measurements. However, the flight paths of the multiple platforms are limited for such an unmanned system since the flight safety and the path length are basic conditions for guaranteeing the effective observation. This paper first studies the observation signal model of MuUAV-SAR imaging system, and then analyzes the factors that determine the imaging resolution, while these factors are all determined by the flight path of UAVs. Secondly, MuUAV-SAR imaging path planning problem is established as a constrained multi-objective optimization problem (CMOP), which considers the navigation and imaging performance of UAV in the process of completing path planning task in detail. For this CMOP, a heuristic search method is proposed to solve it, which can ensure that each step achieves local optimum, and it can also list all feasible solutions to meet the application requirements for selection. Finally, experimental results verify the effectiveness and practicability of the proposed heuristic path planning method.
Highlights
A SYNTHETIC aperture radar (SAR) is widely used in disaster warning, structural mapping, and marine applications with advantages of day and night, all-weather, wideswath, long-range imaging features [1]–[9]
Even when the observation time of a single platform is insufficient, a multistatic unmanned aerial vehicle-borne synthetic aperture radar (MuUAV-SAR) can splice the echo data from multiple transmitters to achieve the same high-resolution observation effect, which is the benefit brought by the MuUAV-SAR, while it brings more resource consumption
OPTIMIZATION PROBLEM FORMULATION AND PATH PLANNING SOLVING FOR THE UAV. Analyzing the factors such as detection task, navigation constraints, and imaging resolution of UAV radar platforms, the UAV path planning problem is established as a constrained multiobjective optimization problem (CMOP)
Summary
A SYNTHETIC aperture radar (SAR) is widely used in disaster warning, structural mapping, and marine applications with advantages of day and night, all-weather, wideswath, long-range imaging features [1]–[9]. XU et al.: HEURISTIC PATH PLANNING METHOD FOR MULTISTATIC UAV-BORNE SAR IMAGING SYSTEM imaging system, which brings higher flexibility to the system, while some problems need to be solved urgently at the same time. In order to further verify the effectiveness and feasibility of the proposed method, further research is carried out, including the following three aspects: 1) the azimuth resolution is discussed detail combined with the MuUAV-SAR imaging model [53]; 2) the analysis of the influence of the weight hyperparameters of the objective function is added; and 3) the imaging effects of the 2-D scenario targets corresponding to different planned paths are compared.
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